Abstract: A method for performing machine learning includes assigning processing jobs to a plurality of model learners, using a central parameter server. The processing jobs includes solving gradients based on a current set of parameters. As the results from the processing job are returned, the set of parameters is iterated. A degree of staleness of the solving of the second gradient is determined based on a difference between the set of parameters when the jobs are assigned and the set of parameters when the jobs are returned. The learning rates used to iterate the parameters based on the solved gradients are proportional to the determined degrees of staleness.

Abstract: A method for performing machine learning includes assigning processing jobs to a plurality of model learners, using a central parameter server. The processing jobs includes solving gradients based on a current set of parameters. As the results from the processing job are returned, the set of parameters is iterated. A degree of staleness of the solving of the second gradient is determined based on a difference between the set of parameters when the jobs are assigned and the set of parameters when the jobs are returned. The learning rates used to iterate the parameters based on the solved gradients are proportional to the determined degrees of staleness.

Abstract: A method includes embedding clothing with at least one sensor and at least one control unit; a power unit powering on the at least one sensor and the at least one control unit; the at least one sensor monitoring a sensed condition; the at least one control unit conducting a heat prediction based on the sensed condition; and the at least one control unit controlling threads within the clothing based on the heat prediction to actively adjust properties of the clothing.

Abstract: A method includes embedding clothing with at least one sensor and at least one control unit; a power unit powering on the at least one sensor and the at least one control unit; the at least one sensor monitoring a sensed condition; the at least one control unit conducting a heat prediction based on the sensed condition; and the at least one control unit controlling threads within the clothing based on the heat prediction to actively adjust properties of the clothing.

Abstract: Mechanisms are provided, in a data processing system having a processor and a transactional memory, for executing a transaction in the data processing system. These mechanisms execute a transaction comprising one or more instructions that modify at least a portion of the transactional memory. The transaction is suspended in response to a transaction suspend instruction being executed by the processor. A suspended block of code is executed in a non-transactional manner while the transaction is suspended. A determination is made as to whether an interrupt occurs while the transaction is suspended. In response to an interrupt occurring while the transaction is suspended, a transaction abort operation is delayed until after the transaction suspension is discontinued.

Abstract: Mechanisms are provided, in a data processing system having a processor and a transactional memory, for executing a transaction in the data processing system. These mechanisms execute a transaction comprising one or more instructions that modify at least a portion of the transactional memory. The transaction is suspended in response to a transaction suspend instruction being executed by the processor. A suspended block of code is executed in a non-transactional manner while the transaction is suspended. A determination is made as to whether an interrupt occurs while the transaction is suspended. In response to an interrupt occurring while the transaction is suspended, a transaction abort operation is delayed until after the transaction suspension is discontinued.